Know why your portfolio breaks, before it does.
PlanckNet decomposes portfolio losses into market moves, liquidity costs, and control failures. Same seed, same crash, every time. Fully debuggable.
Built for hedge funds and asset managers running multi-strategy portfolios where liquidity and controls dominate tail losses.
Determinism you can verify, not just claims.
Every run produces a structured artifact you can diff, replay, and audit. Determinism regression and verification checks keep the kernel honest.
| Field | Run A | Run B |
|---|---|---|
| kernel_version | v18.3.4.2 | v18.3.4.2 |
| seed | 1337 | 1337 |
| steps | 20 | 20 |
| run_hash | 0x9c7a…f21b | 0x9c7a…f21b |
What you get per run
- Decomposed PnL by step: market vs liquidity vs guard intervention
- Replayable trace so failures are debuggable, not statistical
- Verification checks to validate stability, drift, and regime integrity
Engineering appendix (spec excerpt)
STRUCT EngineConfig:
T_max: int
W_drift_window: int
B_CRIT_fin: float
FUNCTION LSO_apply_batched(X_block, prices, orders, depths):
# clamp by depth, compute impact, compute holdings-based dPnL
RETURN dPnL_LSO_block
FUNCTION enforce_stability_PER_LEN(...):
# drift budgets per partition (LEN) with rolling windows
RETURN drift_state, dPnL_stable
END-TO-END: determinism regression
same seed -> identical PnL_logs, regime_logs, scenario_log
Most stress systems produce a report. They do not produce a replayable trace.
VaR aggregates risk. It does not explain it. When a strategy fails, you see the loss, but not the cause.
Black-box metrics
Aggregates hide failure modes. When something breaks, you cannot see what.
Liquidity blindness
Execution costs during stress are handled with crude add-ons, or ignored.
Non-reproducible tests
One-off stress reports cannot be replayed. You cannot debug randomness.
Decomposition is the product.
PlanckNet runs controlled experiments where each step separates market shock, liquidity cost, and control intervention.
RPO (Risk Propagation)
Models how factor shocks propagate through correlated instruments.
LSO (Liquidity Shock)
Quantifies execution cost and market impact under depth and urgency.
Drift Guard System
Testable circuit breakers with rolling PnL budgets per portfolio and partition.
Deterministic kernel
Seeded execution yields identical timelines for identical inputs. Replay and diff become first-class workflows.
Experimental layer
Not replacing vendor suites. PlanckNet runs alongside existing tools as the experimental, explainable stress layer.
A guided, 2-minute proof.
Run the same scenario twice and confirm identical regime timeline and outputs.
VC preset (recommended)
- Preset: Conservative
- Seed: 1337
- Steps: 20
- What to look for: regime flip around steps 5 to 6, then decomposed PnL and guard status
- Verification: run twice and confirm identical timeline
Paid pilots that test falsifiable hypotheses.
The goal is decision-making impact, not feature usage: reproducible stress reports with decomposition, plus an IC-ready walkthrough.
90-day pilot
$5K to $10K per month. Hypothesis-driven deliverables and reproducible artifacts.
Annual license
$100K to $150K ARR. Expansion path across desks, assets, and scenario packs.
Deployment
SaaS today, with VPC and on-prem options for institutional environments.
Initial buyers
Quant research, risk innovation teams, and advanced PMs with discretionary budgets and faster cycles.
Why now
Post-2023 governance pressure, liquidity-driven failures, rising strategy complexity, and brittle internal infra make reproducibility a requirement.
Raising to turn a validated kernel into institutional pilots.
This round funds validation, pilot deployments, and API hardening to reach 2 to 3 paid pilots and seed readiness.
Raise
$200K pre-seed on a SAFE. Details in investor materials.
Use of funds
Validation suite, pilots and conversion, infrastructure and legal, plus buffer.
9-month milestones
Validation and hardening, then 2 to 3 paid pilots, then first ARR and seed prep with case studies.
Download and forward.
One-pager, pitch deck, and memo aligned to the same story as this site.
Research-grade systems that ship.
Three founders covering quantitative modeling, deterministic systems engineering, and institutional go-to-market. Full backgrounds shared on request.
Quant lead
Stress regime design, factor modeling, simulation logic, and methodology validation.
Engineering lead
Deterministic execution, artifact logging, API design, and verification discipline.
Product and BD
Pilot conversion, pricing, design partners, and institutional sales motion.
Book a call or request materials.
Email us and we will reply with scheduling options and the PDF package.
office@coromandus.com
Include your firm, role, and availability.
Live demo
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